Greenfly Aphid Swarm Optimization Algorithm
Hanan A. R. Akkar, Sameem Abbas Salman
Abstract
Open-access reader
Hanan A. R. Akkar, Sameem Abbas Salman
Abstract
Open-access reader
A new metaheuristic swarm intelligence optimization technique, called general greenfly aphid swarm optimization algorithm, which is proposed by enhancing the performance of swarm optimization through cockroach swarm optimization algorithm. The performance of 23 benchmark functions is tested and compared with widely used algorithms, including particle swarm optimization algorithm, cockroach swarm optimization and grasshopper optimization algorithm. Numerical experiments show that the greenfly aphid swarm optimization algorithm outperforms its counterparts. Besides, to demonstrate the practical impact of the proposed algorithm, two classic engineering design problems, namely, pressure vessel design problem and himmelblau’s optimization problem, are also considered and the proposed greenfly aphid swarm optimization algorithm is shown to be competitive in those applications.
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A new metaheuristic swarm intelligence optimization technique, called general greenfly aphid swarm optimization algorithm, which is proposed by enhancing the performance of swarm optimization through cockroach swarm optimization algorithm. The performance of 23 benchmark functions is tested and compared with widely used algorithms, including particle swarm optimization algorithm, cockroach swarm optimization and grasshopper optimization algorithm. Numerical experiments show that the greenfly aphid swarm optimization algorithm outperforms its counterparts. Besides, to demonstrate the practical impact of the proposed algorithm, two classic engineering design problems, namely, pressure vessel design problem and himmelblau’s optimization problem, are also considered and the proposed greenfly aphid swarm optimization algorithm is shown to be competitive in those applications.
Key concepts: Multi-swarm optimization, Metaheuristic, Parallel metaheuristic, Particle swarm optimization, Meta-optimization, Swarm behaviour, Imperialist competitive algorithm, Derivative-free optimization